Implicit Beamforming Weight Computation via Multi-Subcarrier Extraction
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Solution Overview
Problem
In MIMO wireless communication systems, accurately computing downlink beamforming weights is challenging when the destination device does not transmit with its full uplink spatial capability, making it difficult to extract the full dimensional spatial information needed for channel knowledge.
Innovation Solution
A method is provided to compute downlink beamforming weights by deriving values from consecutive subcarriers across multiple antennas, using techniques such as eigenvector and eigenvalue calculations, and applying these weights to spatial streams for downlink transmission, even when the uplink spatial streams are less than the maximum number.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If implicit beamforming weight estimation is used, then overhead and latency are reduced and channel coherency is maintained, but full spatial dimension information cannot be extracted when the destination device does not transmit with full uplink spatial capability
Solution Approach 1:
The patent transitions from extracting spatial information in the time domain to extracting it in the frequency domain by utilizing multiple consecutive subcarriers. This dimensional transformation allows the system to obtain full spatial channel information even when the destination device transmits with fewer than maximum spatial streams, resolving the contradiction between maintaining implicit beamforming benefits and extracting complete spatial information.
Solution Approach 2:
The patent performs preliminary actions by receiving and processing multiple consecutive subcarriers before computing the final beamforming weights. By accumulating information across multiple subcarriers in advance, the system builds sufficient spatial dimension knowledge without requiring the destination device to transmit at full spatial capability, thus maintaining low latency while extracting complete spatial information.
2Use of energy by moving object
If the destination device transmits with fewer than maximum spatial streams, then energy consumption is reduced and implementation flexibility is improved, but full dimensional spatial information extraction becomes difficult
Solution Approach 1:
The patent resolves the contradiction by moving the spatial information extraction process to the frequency domain through multi-subcarrier processing. This allows the system to reconstruct full dimensional spatial information from transmissions with fewer spatial streams, maintaining measurement precision while enabling energy-efficient operation at reduced spatial stream counts.
Solution Approach 2:
The patent applies continuity by processing multiple consecutive subcarriers in sequence to accumulate sufficient spatial information. This continuous processing across frequency resources enables the system to maintain accurate spatial information extraction even when the number of active spatial streams is reduced, thus preserving measurement precision while reducing energy consumption.
3Productivity
If beamforming weights are computed using full uplink spatial capability, then downlink transmission performance is optimized, but system complexity increases and adaptability to varying spatial stream configurations is reduced
Solution Approach 1:
The patent simplifies the system by transforming the beamforming weight computation from a complex matrix operation requiring full spatial capability to a more straightforward process using multi-subcarrier received signals. This frequency-domain approach maintains downlink transmission performance while significantly reducing the computational complexity and adaptability requirements of the system.
Solution Approach 2:
The patent enables the system to self-adjust by automatically extracting spatial information from the actual uplink transmission configuration without requiring explicit configuration of full spatial capability. The multi-subcarrier processing inherently adapts to varying spatial stream configurations, maintaining optimal downlink performance while reducing the need for complex system configuration and management.
Data Source
AI summary
Techniques are provided to compute downlink beamforming weights for beamforming multiple spatial streams to a wireless device when that wireless device does not transmit with a maximum number of spatial streams, and thus when the full dimensional knowledge of the wireless channel to that wireless device needs to be implicitly derived. Uplink signals are received at a plurality of antennas of a first wireless device that are transmitted via a plurality of antennas of a second wireless device. The first wireless device derives values at a plurality of subcarriers of the received signals across the plurality of antennas of the first wireless device. Downlink beamforming weights are computed from values of consecutive subcarriers across the plurality of antennas of the first wireless device. The first wireless device applies the downlink beamforming weights at respective subcarriers to a number of spatial streams to be transmitted to the second wireless device.